State detection system for internal combustion engine, data analysis device, and vehicle

ABSTRACT

A state detection system for an internal combustion engine includes: a memory configured to store mapping data, the mapping data being data that defines a detection mapping, the detection mapping being a mapping between an input and an output, the input being a rotation waveform variable and a drive system rotation speed variable and the output being a value of a combustion state variable, and the detection mapping including a joint operation of the rotation waveform variable and the drive system rotation speed variable based on a parameter learned by machine learning; and a processor configured to execute an acquisition process and a determination process, the acquisition process being configured to acquire a value of the drive system rotation speed variable, the determination process being configured to determine whether or not the internal combustion engine is in a predetermined operating state.

INCORPORATION BY REFERENCE

The disclosure of Japanese Patent Application No. 2019-141882 filed onAug. 1, 2019 including the specification, drawings and abstract isincorporated herein by reference in its entirety.

BACKGROUND 1. Technical Field

The present disclosure relates to a system for detecting an operatingstate involving variation in combustion state between cylinders in aninternal combustion engine mounted on a vehicle, a data analysis deviceconstituting the system, and a vehicle.

2. Description of Related Art

In internal combustion engines, when the combustion states of cylindersvary due to a misfire, a variation in air-fuel ratio, or the like,rotation fluctuation of a crankshaft increases. Accordingly, it ispossible to detect the misfire, the variation in air-fuel ratio, or thelike based on the rotation fluctuation patterns of the crankshaft. Forexample, Japanese Patent Application Publication No. 4-91348 discloses amisfire detection system that detects a misfire using a hierarchicalneural circuit model. The hierarchical neural circuit model isconfigured such that time series data, obtained by sampling the rotationspeed of a crankshaft of an internal combustion engine in each givencycle, is input into an input layer, and information on the cylinderwhere a misfire has occurred is output from an output layer.

SUMMARY

Now, in an internal combustion engine mounted on a vehicle, a drivesystem that transmits motive power to driving wheels influences therotation behavior of a crankshaft. There is a concern that suchinfluence may deteriorate the accuracy of detecting a misfire or thelike based on the rotation fluctuation patterns of the crankshafts asdescribed above.

A state detection system for an internal combustion engine according toa first aspect of the present disclosure is applied to the internalcombustion engine mounted on a vehicle. The state detection system isconfigured to detect a predetermined operating state of the internalcombustion engine that involves a variation in combustion state betweencylinders. The state detection system includes: a memory; and aprocessor. The memory is configured to store mapping data. The mappingdata is data that defines a detection mapping, the detection mappingbeing a mapping between an input and an output, the input being arotation waveform variable and a drive system rotation speed variableand the output being a value of a combustion state variable, and thedetection mapping including a joint operation of the rotation waveformvariable and the drive system rotation speed variable based on aparameter learned by machine learning. The rotation waveform variable isa variable including information on a difference in rotation speed of acrankshaft between the cylinders of the internal combustion engineduring a period when combustion torque is generated in each of thecylinders. The drive system rotation speed variable is a variableindicating information on a rotation speed of a drive system rotatingelement that is a rotating element disposed in a power transmission linebetween the internal combustion engine and driving wheels. Thecombustion state variable is a variable relating to a variation degreein combustion state between the cylinders. The processor is configuredto execute an acquisition process and a determination process. Theacquisition process is configured to acquire a value of the rotationwaveform variable based on an output of a sensor that detects rotationbehavior of the crankshaft and to acquire a value of the drive systemrotation speed variable based on an output of a sensor that detectsrotation behavior of the drive system rotating element. Thedetermination process is configured to determine whether or not theinternal combustion engine is in the predetermined operating state,based on an output value of the detection mapping that takes the valuesof the rotation waveform variable and the drive system rotation speedvariable acquired in the acquisition process as an input.

When the combustion state varies between the cylinders, the combustiontorque in each of the cylinders becomes different, which causes adifference in rotation speed of the crankshaft between the cylinders,during the period when combustion torque is generated in each of thecylinders. The information on such difference in rotation speed of thecrankshaft between the cylinders can be acquired from the output of thesensor that detects the rotation behavior of the crankshaft. When thedifference in rotation speed of the crankshaft between the cylindersduring the period of combustion torque generation is simply caused byonly a variation in combustion torque between the cylinders, it ispossible to accurately detect, from the information on the difference inrotation speed between the cylinders, the operating state of theinternal combustion engine that involves a variation in combustion stateof the cylinders due to a misfire, an air-fuel ratio imbalance betweenthe cylinders, or the like. Under these circumstances, in the aboveconfiguration, in consideration that the variation in combustion statebetween cylinders causes a difference in rotation speed of thecrankshaft during the combustion torque generation period, an input tothe detection mapping includes the rotation waveform variable includingthe information on the difference in rotation speed between cylinders.

Meanwhile, in the internal combustion engine mounted on the vehicle, thedrive system that transmits the motive power of the internal combustionengine to the driving wheels influences the rotation behavior of thecrankshaft. To cope with this situation, in the above configuration, theinput to the detection mapping also includes the drive system rotationspeed variable indicating information on the rotation speed of a drivesystem rotating element that is a rotating element disposed in a powertransmission line between the internal combustion engine and the drivingwheels. In the configuration, the presence or absence of an occurrenceof the predetermined operating state is determined based on the value ofa combustion state variable calculated through join operation of therotation waveform variable and the drive system rotation speed variablebased on a parameter learned by machine learning. The parameter referredherein can be learned based on the presence or absence of an occurrenceof the predetermined operating state when the rotation waveform variableand the drive system rotation speed variable as described above takevarious values. Accordingly, the state detection can be conducted bytaking the influence that the drive system exerts on the rotationbehavior of the crankshaft into accounts. Therefore, the detectingaccuracy of the predetermined operating state in the internal combustionengine mounted on the vehicle can be enhanced.

In the above aspect, the predetermined operating state may be a statewhere a misfire has occurred. In the above aspect, the predeterminedoperating state may be a state where an air-fuel ratio varies betweenthe cylinders. In the aspect, the drive system rotating element may be atransmission input shaft. Incidentally, examples of the drive systemrotating element that can provide the rotation speed may include atransmission output shaft and a driving wheel shaft, in addition to thetransmission input shaft.

In the above aspect, the drive system rotation speed variable may be avariable indicating time series data of the rotation speed of the drivesystem rotating element. In this case, it becomes possible to detect therotation fluctuation that reflects a delay until the change in rotationspeed of the drive system rotating element influences the rotationbehavior of the crankshaft.

In the above aspect, when it is determined by the determination processthat the internal combustion engine is in the predetermined operatingstate, the processor may be configured to operate prescribed hardware toexecute a handling process for handling the predetermined operatingstate. The handling process includes, for example, a process ofnotifying an occupant that the internal combustion engine is in thepredetermined operating state, and a process of elimination or reducingthe predetermined operating state.

In the above aspect, the determination process may include an outputvalue calculation process for calculating an output value of thedetection mapping that takes the values of the rotation waveformvariable and the drive system rotation speed variable acquired in theacquisition process as an input. The processor may include a firstprocessor mounted on the vehicle, and a second processor disposedoutside the vehicle. The first processor may be configured to executethe acquisition process and a vehicle-side reception process forreceiving a signal based on a calculation result of the output valuecalculation process. The second processor may be configured to executethe output value calculation process and an outer-side transmissionprocess for transmitting to the vehicle a signal based on thecalculation result of the output value calculation process. In thiscase, the output value calculation process that is high in arithmeticload is performed outside the vehicle.

A data analysis device according to a second aspect of the presentdisclosure includes the second processor and the memory.

A vehicle according to a third aspect of the present disclosure includesthe first processor.

BRIEF DESCRIPTION OF THE DRAWINGS

Features, advantages, and technical and industrial significance ofexemplary embodiments of the disclosure will be described below withreference to the accompanying drawings, in which like numerals denotelike elements, and wherein:

FIG. 1 schematically shows the configuration of a state detection systemaccording to a first embodiment and a drive system of a vehicle thatincorporates an internal combustion engine to which the state detectionsystem is applied;

FIG. 2 is a flowchart of a process defined as a misfire program executedby a controller provided in the state detection system of the firstembodiment;

FIG. 3 shows a setting mode of input variables of a mapping in theembodiment;

FIG. 4 is a flowchart showing some of the process defined as a misfireprogram that is executed by the controller provided in the statedetection system according to a second embodiment;

FIG. 5 schematically shows the configuration of the state detectionsystem according to a third embodiment;

FIG. 6 is a flowchart of a vehicle-side process in the state detectionsystem;

FIG. 7 is a flowchart of a center-side process in the state detectionsystem;

FIG. 8 is a flowchart of a process defined as a detection programexecuted by the controller provided in the state detection systemaccording to a fourth embodiment; and

FIG. 9 is a flowchart of a process defined as a handling program that isexecuted by the controller.

DETAILED DESCRIPTION OF EMBODIMENTS First Embodiment

Hereinafter, a first embodiment of a state detection system for aninternal combustion engine will be described in detail with reference toFIGS. 1 to 3.

In an internal combustion engine 10 mounted on a vehicle VC shown inFIG. 1, an intake passage 12 is equipped with a throttle valve 14. Theair taken in from the intake passage 12 flows into combustion chambers18 of cylinders #1 to #4, when intake valves 16 are opened. Fuel isinjected into the combustion chambers 18 with fuel injection valves 20.In the combustion chambers 18, mixture of air and fuel is used forcombustion through spark discharge by ignition devices 22. Energygenerated by combustion is taken out as rotational energy of acrankshaft 24. The air-fuel mixture used for combustion is discharged toan exhaust passage 28 as an exhaust gas, when exhaust valves 26 areopened.

The crankshaft 24 is joined with a crank rotor 30 provided with aplurality of (thirty-four herein) tooth portions 32 indicative of arotation angle of the crankshaft 24. Although the crank rotor 30 isbasically provided with the tooth portions 32 at intervals of 10° CA, anuntoothed portion 34 is provided in a spot where an interval with theadjacent tooth portions 32 is 30° CA. The untoothed portion 34 isprovided to indicate a reference rotation angle of the crankshaft 24. Inthe vicinity of the crank rotor 30, a crank angle sensor 72 is disposed.The crank angle sensor 72 converts a change in magnetic flux,corresponding to approach and separation of the tooth portions 32, intoa pulse signal with a square wave, and outputs the pulse signal. In thefollowing description, such an output signal of the crank angle sensor72 is stated as a crank signal Scr. In the present embodiment, the crankangle sensor 72 corresponds to the sensor that detects the rotationbehavior of the crankshaft 24.

A change gear 44 is provided in a power transmission line from thecrankshaft 24 of the internal combustion engine 10 to driving wheels 50of the vehicle VC. The change gear 44 has a transmission input shaft 45that is an input shaft of the motive power from the crankshaft 24, and atransmission output shaft 46 that is an output shaft of the motive powertoward the driving wheels 50. Through hydraulic control by a hydrauliccircuit 48, the change gear 44 changes a gear ratio that is a ratio ofthe rotation speed of the transmission output shaft 46 to the rotationspeed of the transmission input shaft 45. The change gear 44 is equippedwith an input shaft speed sensor 76 that detects an input shaft rotationspeed NT that is the rotation speed of the transmission input shaft 45,and an output shaft speed sensor 77 that detects an output shaft speedNout that is the rotation speed of the transmission output shaft 46.Incidentally, the change gear 44 may be one of a stepped change gearthat discretely switches the gear ratio and a stepless transmission thatcontinuously switches the gear ratio.

In a portion of the power transmission line between the crankshaft 24and the transmission input shaft 45, a torque converter 40 is provided.The torque converter 40 transmits torque between the crankshaft 24 andthe transmission input shaft 45 through oil that is filled therein. Thetorque converter 40 is also equipped with a lock-up clutch 42. When thelock-up clutch 42 is engaged, torque is directly transmitted to thetransmission input shaft 45 from the crankshaft 24 without through theoil. The engagement of the lock-up clutch 42 is controlled by adjustmentof a lock-up hydraulic pressure Plc by the hydraulic circuit 48.

The vehicle VC further includes a controller 60. The controller 60includes a CPU 62, a ROM 64, a memory 66 that is an electricallyrewritable nonvolatile memory, and a peripheral circuit 67, which cancommunicate with each other through a bus 68. The peripheral circuit 67includes a circuit for generating a clock signal that defines internaloperation, an electric power source circuit, and a reset circuit.

The controller 60 controls the internal combustion engine 10. In orderto control controlled variables such as torque and an exhaust gascomponent ratio, the controller 60 operates operation units, such as thethrottle valve 14, the fuel injection valves 20, and the ignitiondevices 22 of the internal combustion engine 10. The controller 60 alsocontrols the change gear 44. In order to control the controlled variablethat is the gear ratio, the controller 60 operates the hydraulic circuit48. The controller 60 further controls the lock-up clutch 42. In orderto control the controlled variable that is the lock-up hydraulicpressure Plc, the controller 60 operates the hydraulic circuit 48. Thecontroller 60 controls the internal combustion engine 10, the changegear 44, and the lock-up clutch 42 by causing the CPU 62 to executeprograms stored in the ROM 64. In FIG. 1, operation signals MS1 to MS4of the throttle valve 14, the fuel injection valves 20, the ignitiondevices 22, and the hydraulic circuit 48 are illustrated.

When controlling the controlled variables as described above, thecontroller 60 refers to an intake air amount Ga detected by an airflowmeter 70, the crank signal Scr of the crank angle sensor 72, anaccelerator operation amount ACCP that is a depression amount of anaccelerator pedal detected by an accelerator sensor 74, and an operationposition Sft of a shift lever detected by a shift position sensor 75.The controller 60 also refers to the lock-up hydraulic pressure Plcdetected by an oil pressure sensor 73 provided in the hydraulic circuit48, the input shaft rotation speed NT detected by the input shaft speedsensor 76, the output shaft speed Nout detected by the output shaftspeed sensor 77, a wheel speed V that is the rotation speed of thedriving wheels 50 detected by the wheel speed sensor 79, or the like.The exhaust passage 28 is equipped with an air-fuel ratio sensor 71.When controlling the controlled variables, the controller 60 also refersto a detection value of the air-fuel ratio sensor 71. Incidentally, theair-fuel ratio sensor 71 outputs a detection signal corresponding to thecomponents of exhaust gas before being cleaned by an exhaust gascleaning catalyst. The detection value corresponds to the air-fuel ratioof an air-fuel mixture combusted in the combustion chambers 18 of thecylinders #1 to #4. In the following description, the detection value ofthe air-fuel ratio sensor 71 is stated as an upstream-side detectionvalue Afu.

When controlling the controlled variables, the controller 60 also refersto the rotation speed NE of the crankshaft 24. The CPU 62 calculates therotation speed NE of the crankshaft 24 based on the aforementioned cranksignal Scr. Incidentally, the rotation speed NE is desirably an averagevalue of the rotation speeds when the crankshaft 24 rotates by arotation angle equal to or greater than one rotation of the crankshaft24. Without being limited to the value obtained by simple arithmeticaverage, the average value may be obtained by, for example, an indexmoving average process. In that case, the average value is calculatedbased on time series data of the crank signal Scr when the crankshaft 24rotates by a rotation angle of one rotation or more.

Furthermore, while the internal combustion engine 10 is in operation,the controller 60 determines the presence or absence of a misfire. Inthe present embodiment, the controller 60 that detects the presence orabsence of such a misfire corresponds to the state detection system.

FIG. 2 shows the procedure of a process relating to detection of amisfire. The process shown in FIG. 2 is implemented when the CPU 62repeatedly executes a misfire program 64 a stored in the ROM 64 in everycontrol cycle. Hereinafter, the step number of each process will beexpressed by numerals prepended with “S”.

In a series of processes shown in FIG. 2, the CPU 62 first acquiresminute rotation time T30 (S10). The CPU 62 calculates the minuterotation time T30 by checking the time taken for the crankshaft 24 torotate by 30° CA, based on the crank signal Scr of the crank anglesensor 72. Next, the CPU 62 sets latest minute rotation time T30acquired in the process of S10 as minute rotation time T30(0). As theminute rotation time T30 is older, a variable “m” in the minute rotationtime T30(m) becomes larger (S12). More specifically, on the assumptionthat “m=1, 2, 3, . . .”, minute rotation time T30(m-1) immediatelybefore execution of the process of S12 is defined as minute rotationtime T30(m). Hence, for example, the minute rotation time T30, acquiredin the process of S10 when the process of FIG. 2 is executed last time,becomes minute rotation time T30(1).

Next, the CPU 62 determines whether or not the minute rotation time T30acquired in the process of S10 is equal to the time taken for rotationat an angular interval from 30° CA before a compression top dead centerto the compression top dead center in any one of the cylinders #1 to #4(S14). When determining that the minute rotation time T30 is the timetaken for rotation at the angular interval to the compression top deadcenter (S14: YES), the CPU 62 first calculates a value of a rotationwaveform variable as an input of the process of determining the presenceor absence of a misfire so as to determine the presence or absence of amisfire in the cylinder that has reached the compression top dead centerbefore 360° CA.

Specifically, the CPU 62 first calculates, as an inter-cylinder variableΔTa, a difference between values of the minute rotation time T30relating to the angular interval from 30° CA before the compression topdead center to the compression top dead center, the values beingseparated by 180° from each other (S16). More specifically, on theassumption that “m=1, 2, 3. . .”, the CPU 62 sets an inter-cylindervariable ΔTa(m−1) to “T30(6m−6)−T30(6m)”.

FIG. 3 illustrates the inter-cylinder variable ΔTa. In the presentembodiment, the compression top dead center appears in order of thecylinder #1, the cylinder #3, the cylinder #4, and the cylinder #2, andpower stroke starts in this order. FIG. 3 indicates that the target fordetecting the presence or absence of a misfire is the cylinder #1 byacquiring the minute rotation time T30 of the cylinder #4 at an angularinterval from 30° CA before the compression top dead center to thecompression top dead center in the process of S10. In this case, aninter-cylinder variable ΔTa(0) is a difference between the minuterotation time T30 corresponding to the compression top dead center ofthe cylinder #4 and the minute rotation time T30 corresponding to thecompression top dead center of the cylinder #3 which was at thecompression top dead center before the cylinder #4. FIG. 3 indicatesthat an inter-cylinder variable ΔTa(2) is a difference between theminute rotation time T30(12) corresponding to the compression top deadcenter of the cylinder #1 that is a detection target of a misfire andthe minute rotation time T30(18) corresponding to the compression topdead center of the cylinder #2.

With reference to FIG. 2 again, the CPU 62 calculates an inter-cylindervariable ΔTb that is a difference between values separated by 720° CAfrom each other, out of the inter-cylinder variables ΔTa(0), ΔTa(1), ΔTa(2), . . . (S18). Specifically, on the assumption that “m=1, 2, 3. . .”,the CPU 62 sets an inter-cylinder variable ΔTb(m−1) to “ΔTa(m−1)−ΔTa(m+3)”.

FIG. 3 illustrates the inter-cylinder variable ΔTb. In FIG. 3, theinter-cylinder variable ΔTb(2) is stated as “ΔTa(2)-Ta(6).” Next, theCPU 62 calculates a fluctuation pattern variable FL indicating arelative size relation between the inter-cylinder variable ΔTbcorresponding to the cylinder that is the detection target of a misfireand the inter-cylinder variable ΔTb corresponding to other cylinders(S20). In the present embodiment, fluctuation pattern variables FL[02],FL[12], FL[32] are calculated.

Here, the fluctuation pattern variable FL[02] is defined by“ΔTb(0)/ΔTb(2).” More specifically, when the example of FIG. 3 is used,the fluctuation pattern variable FL[02] is a value obtained by dividingthe inter-cylinder ΔTb(0), corresponding to the cylinder #4 that will beat the compression top dead center after the cylinder#1 and cylinder #3,by the inter-cylinder ΔTb(2) corresponding to the cylinder #1 that isthe detection target of a misfire. The fluctuation pattern variableFL[12] is defined by “ΔTb(1)/ΔTb(2).” More specifically, when theexample of FIG. 3 is used, the fluctuation pattern variable FL[12] is avalue obtained by dividing an inter-cylinder ΔTb(1), corresponding tothe cylinder #3 that will be at the compression top dead center afterthe cylinder#1, by the inter-cylinder ΔTb(2) corresponding to thecylinder #1 that is the detection target of a misfire. The fluctuationpattern variable FL[32] is defined by “ΔTb(3)/ΔTb(2).” Morespecifically, when the example of FIG. 3 is used, the fluctuationpattern variable FL[32] is a value obtained by dividing aninter-cylinder ΔTb(3), corresponding to the cylinder #2 that was at thecompression top dead center before the cylinder#1, by the inter-cylinderΔTb(2) corresponding to the cylinder #1 that is the detection target ofa misfire.

In the present embodiment, the thus-calculated values of theinter-cylinder ΔTb(2), and the fluctuation pattern variables FL[02], FL[12], FL [32] are used as information on a difference in rotation speedof the crankshaft 24 between the cylinders during the period whencombustion torque is generated in each of the cylinders.

Next, the CPU 62 acquires values of the rotation speed NE, a chargingefficiency η, the lock-up hydraulic pressure Plc, and the input shaftrotation speed NT (S22). The CPU 62 then substitutes the value of therotation waveform variable acquired in the processes of S18, S20, andthe values of the variable acquired in the process of S22 into inputvariables x(1) to x(8) of a mapping that outputs a combustion statevariable PR that is a variable regarding the probability of occurrenceof a misfire in the cylinder that is a detection target (S24).Specifically, in the process of S24, the CPU 62 substitutes the value ofthe inter-cylinder ΔTb(2) into the input variable x(1), the value of thefluctuation pattern variable FL[02] into the input variable x(2), thevalue of the fluctuation pattern variable FL[12] into the input variablex(3), and the value of the fluctuation pattern variable FL[32] into theinput variable x(4), respectively. The CPU 62 also substitutes the valueof the rotation speed NE into the input variable x(5), the value of thecharging efficiency η into the input variable x(6), the value of thelock-up hydraulic pressure Plc into the input variable x(7), and thevalue of the input shaft rotation speed NT into the input variable x(8).

Next, the CPU 62 inputs the values of the input variables x(1) to x(8)into the mapping that is defined by mapping data 66 a stored in thememory 66 shown in FIG. 1 so as to calculate the value of the combustionstate variable PR that is an output value of the mapping (S26).

In the present embodiment, the mapping is constituted of a neuralnetwork having one intermediate layer. The neural network includes anactivation function h(x) as an input-side nonlinear mapping thatperforms nonlinear conversion of the outputs of an input-sidecoefficient wFjk (j=0 to n, k=0 to 8) and an input-side linear mappingthat is a linear mapping defined by the input-side coefficient wFjk. Inthe present embodiment, a function ReLU is illustrated as the activationfunction h(x). The function ReLU outputs a larger one of an input and“0”. Incidentally, the coefficient wFj0 or the like is a bias parameter,and the input variable x(0) is defined as “1”. In the followingdescription, the mapping is stated as a detection mapping.

The neural network includes a softmax function that outputs thecombustion state variable PR that takes output-side coefficient wSij(i=1 to 2, j=0 to n) and prototype variables yR(1), yR(2) as inputs, theprototype variables yR(1), yR(2) being an output of an output-sidelinear mapping that is a linear mapping defined by the output-sidecoefficient wSij. Hence, in the present embodiment, the combustion statevariable PR is a value representing the magnitude of likelihood that amisfire has actually occurred, the value being quantified as acontinuous value in a specified region larger than “0” and smaller than“1”.

Next, the CPU 62 determines whether or not the value of the combustionstate variable PR is equal to or larger than a determination value PRth(S28). When determining that the value of the combustion state variablePR is equal to or larger than the determination value PRth (S28: YES),the CPU 62 increments a counter CR (S30). The CPU 62 then determineswhether or not a prescribed period has lapsed from the time when theprocess of S28 was first executed or from the time when a process of S36described later was executed (S32). Here, the prescribed period islonger than the period of one combustion cycle, and is desirably tentimes as long as one combustion cycle or longer.

When determining that the prescribed period has lapsed (S32: YES), theCPU 62 determines whether or not the counter CR is equal to or greaterthan the threshold CRth (S34). The process of S34 is a process ofdetermining whether or not a misfire has occurred at frequency beyond anallowable range. When determining that the counter CR is less than thethreshold CRth (S34: NO), the CPU 62 initializes the counter CR (S36).On the contrary, when determining that the counter CR is equal to orgreater than the threshold CRth (S34 : YES), the CPU 62 executes anotification process for operating an alarm lamp 78 shown in FIG. 1 inorder to encourage a user to cope with the abnormality (S38).

When the processes of S36, S38 are completed, or when negativedetermination is made in the processes of S14, S28, S32, the CPU 62temporarily terminates a series of the processes shown in FIG. 2.Incidentally, the mapping data 66 a is generated as shown below, forexample. That is, the internal combustion engine 10 coupled with thetorque converter 40 is installed on a test bench, with a dynamometerbeing connected to the output shaft of the torque converter 40. Then,the internal combustion engine 10 is operated on the test bench, andfuel injection is stopped at a timing randomly selected out of thetiming when fuel injection is requested in each of the cylinders #1 to#4. In the cylinder where fuel injection is stopped, data on thecombustion state variable PR having a value of “1” is used as teacherdata, while in the cylinders where fuel injection is not stopped, dataon the combustion state variable PR having a value of “0” is included inteacher data. With use of the rotation waveform variable acquired eachtime and the value acquired in the process of S22, the value of thecombustion state variable PR is calculated by the same processes as inS24, S26. The values of the input-side coefficient wFjk and theoutput-side coefficient wSij are learned so as to reduce a differencebetween the thus-learned combustion state variable PR and the teacherdata. Specifically, the values of the input-side coefficient wFjk andthe output-side coefficient wSij may be learned so as to minimize crossentropy, for example. The input shaft rotation speed NT can be imitatedwith the rotation speed of the dynamometer.

Here, the functions and effects of the present embodiment will bedescribed. When a misfire occurs in the internal combustion engine 10,combustion torque becomes different between cylinders, which causes anincreased fluctuation of the minute rotation time T30. Meanwhile, thecrankshaft 24 is coupled with the drive system of the vehicle VC thatconstitutes the power transmission line from the crankshaft 24 to thedriving wheels 50, and such a drive system influences the rotationbehavior of the crankshaft 24. Under these circumstances, in the statedetection system of the present embodiment, an input to the detectionmapping includes the rotation waveform variable including theinformation on the inter-cylinder difference in rotation speed NE, inconsideration that the variation in combustion state between cylinderscauses an inter-cylinder difference in rotation speed NE of thecrankshaft 24 during the combustion torque generation period.

Meanwhile, in the internal combustion engine 10 mounted on the vehicleVC, the drive system that transmits the motive power of the internalcombustion engine 10 to the driving wheels 50 exerts an influence on therotation behavior of the crankshaft 24. As a solution, in the presentembodiment, the lock-up hydraulic pressure Plc and the input shaftrotation speed NT, which are the state quantities of the drive system,are included in the input variables of the detection mapping.

In the present embodiment, the presence or absence of a misfire isdetermined based on the value of the combustion state variable PR thatis calculated by join operation of the rotation waveform variable, thelock-up hydraulic pressure Plc, and the input shaft rotation speed NT,based on the mapping data 66 a learned by machine learning. The mappingdata 66 a here can be learned based on the presence or absence of amisfire when each of the rotation waveform variable, the lock-uphydraulic pressure Plc, and the input shaft rotation speed NT takevarious values. Accordingly, misfire detection can be conducted bytaking the influence that the drive system exerts on the rotationbehavior of the crankshaft 24 into accounts. Therefore, it is possibleto enhance the detection accuracy of the misfire in the internalcombustion engine 10 mounted on the vehicle VC.

According to the present embodiment described in the foregoing, theoperational effects as described below are further achieved. (1) Therotation speed NE and the charging efficiency as operating pointvariables that define the operating point of the internal combustionengine 10 are used as an input of the detection mapping. The operationamount of the operation units of the internal combustion engine 10, suchas the fuel injection valves 20 or the ignition devices 22, tends to bedetermined based on the operating point of the internal combustionengine 10. Accordingly, the operating point variables are variablesincluding the information regarding the operation amount of each of theoperation units. Therefore, when the operating point variables are usedas an input of the detection mapping, the value of the combustion statevariable PR can be calculated based on the information regarding theoperation amount of each of the operation units. As a result, the valueof the combustion state variable PR can be calculated with higheraccuracy since the rotation behavior of the crankshaft 24 changed by theoperation amount is reflected on the combustion state variable PR.

When the operating point variables are used as input variables, thevalue of the combustion state variable PR is calculated through joinoperation of the rotation waveform variable and the operating pointvariable with use of the input-side coefficient wFjk that is a parameterlearned by machine learning. Accordingly, it is not required to adapt anadaptation value for every operating point variable. Contrary to this,in the case where, for example, size comparison between theinter-cylinder variable ΔTb and a determination value is performed, itis required to adapt the determination value for every operating pointvariable, which causes an increased number of adaptable processes.

(2) The lock-up hydraulic pressure Plc and the input shaft rotationspeed NT are included in the input variables of the detection mapping.This makes it possible to calculate the value of the combustion statevariable PR as a value reflecting the influence that the drive system ofthe vehicle VC exerts on the rotation fluctuation of the crankshaft 24,and by extension to achieve high-accuracy misfire detection reflectingthe influence.

(3) The rotation waveform variable used as an input variable x isgenerated by selectively using the values of the minute rotation timeT30 in the vicinity of the compression top dead center. The values ofthe minute rotation time T30 that show a largest difference due to thepresence or absence of a misfire is the values in the vicinity of thecompression top dead center. Accordingly, selectively using the valuesin the vicinity of the compression top dead center, out of the values ofthe minute rotation time T30, can restrain the dimension of the inputvariable x from increasing, and can take in the information necessaryfor determination of the presence or absence of a misfire as much aspossible.

(4) The rotation waveform variable includes the inter-cylinder ΔTb(2).The inter-cylinder ΔTb(2) is a difference in values of the minuterotation time T30 in the vicinity of the compression top dead centerbetween a cylinder that is the target of misfire detection and acylinder adjacent thereto, the difference being quantified in onedimension in advance. Accordingly, the information necessary fordetermination of the presence or absence of a misfire can efficiently betaken in with a variable having a small number of dimensions.

(5) The rotation waveform variable includes the fluctuation patternvariable FL in addition to the inter-cylinder ΔTb(2). Since vibrationfrom a road surface, or the like, is overlapped on the crankshaft 24,there is a concern that erroneous determination may be made, if only theinter-cylinder ΔTb(2) is used as the rotation waveform variable. As asolution, in the present embodiment, the value of the combustion statevariable PR is calculated using the fluctuation pattern variable FL inaddition to the inter-cylinder ΔTb(2). Accordingly, as compared with thecase where the value of the combustion state variable PR is calculatedonly from the inter-cylinder ΔTb(2), the value of the combustion statevariable PR can be presented as a value that indicates more accuratedegree of likelihood (probability) that a misfire occurred.

Furthermore, in the present embodiment, the value of the combustionstate variable PR is calculated through join operation of theinter-cylinder ΔTb(2) and the fluctuation pattern variable FL with useof the input-side coefficient wFjk that is a parameter learned bymachine learning. Accordingly, as compared with the case where thepresence or absence of a misfire is determined based on the comparisonbetween the inter-cylinder ΔTb(2) and the determination value, and onthe comparison between the fluctuation pattern variable FL and thedetermination value, the presence or absence of a misfire can bedetermined based on a more detailed relationship between the variablesincluding the inter-cylinder ΔTb(2) and the fluctuation pattern variableFL, and the misfire.

Second Embodiment

Hereinafter, a second embodiment of the state detection system for aninternal combustion engine will be described with the attention mainlygiven to the differences from the first embodiment with reference to thedrawings. The state detection system of the present embodiment issimilar in configuration to that of the first embodiment except for thecontents of the misfire program 64 a stored in the ROM 64, and themapping data 66 a stored in the memory 66.

The CPU 62 in the state detection system of the present embodimentconducts as a process relating to misfire detection the process shown inFIG. 2 with some modifications. FIG. 4 shows modified portions of theprocess. Specifically, in the present embodiment, a process of S22′ inFIG. 4 is conducted subsequent to the process of S20 in FIG. 2. Afterthe processes of S24′, S26′ in FIG. 4 are conducted, the processessubsequent to S28 in FIG. 2 are conducted.

In the process of S22′ in FIG. 4, the CPU 62 acquires values of therotation speed NE, the charging efficiency the lock-up hydraulicpressure Plc, and drive system rotation speed variables NT(1) to NT(24).In the drive system rotation speed variables NT(1) to NT(24), followingvalues are stored, respectively. Note that “N” in the followingdescription represents any natural numbers from two to twenty four.Specifically, in every prescribed sampling cycle, the CPU 62 acquiresthe input shaft rotation speed NT from the output of the input shaftspeed sensor 76, and substitutes the acquired value into the drivesystem rotation speed variable NT(1). At the time, the CPU 62substitutes a previous value of the drive system rotation speed variableNT(N-1) into the drive system rotation speed variable NT(N). Thus, thetime series data of input shaft rotation speed NT in every samplingcycle is stored in the drive system rotation speed variables NT(1) toNT(24).

In the subsequent process of S24′, the CPU 62 substitutes the value ofthe rotation waveform variable acquired in the processes of S18, S20 inFIG. 2 and the values of the variables acquired in the process of S22′into input variables x(1) to x(31) of the detection mapping defined bythe mapping data 66 a stored in the memory 66. Specifically, in theprocess of S24′, the CPU 62 substitutes the value of the inter-cylinderΔTb(2) into the input variable x(1), the value of the fluctuationpattern variable FL[02] into the input variable x(2), the value of thefluctuation pattern variable FL[12] into the input variable x(3), andthe value of the fluctuation pattern variable FL[32] into the inputvariable x(4), respectively. The CPU 62 also substitutes the value ofthe rotation speed NE into the input variable x(5), the value of thecharging efficiency η into the input variable x(6), and the value of thelock-up hydraulic pressure Plc into the input variable x(7). The CPU 62further substitutes the values of the drive system rotation speedvariables NT(1) to NT(24) into the input variables x(8) to x(31),respectively.

Next, the CPU 62 inputs the values of the input variables x(1) to x(31)into the detection mapping that is defined by the mapping data 66 a soas to calculate the value of the combustion state variable PR that is anoutput value of the detection mapping (S26′).

Such a detection mapping in the present embodiment is constituted of aneural network having one intermediate layer. The neural networkincludes an activation function h(x) as an input-side nonlinear mappingthat performs nonlinear conversion of the outputs of an input-sidecoefficient wFjk (j=0 to n, k=0 to 31) and an input-side linear mappingthat is a linear mapping defined by the input-side coefficient wFjk. Theneural network also includes a softmax function that outputs thecombustion state variable PR that takes output-side coefficient wSij(i=1 to 2, j=0 to n) and prototype variables yR(1), yR(2) as inputs, theprototype variables yR(1), yR(2) being an output of an output-sidelinear mapping that is a linear mapping defined by the output-sidecoefficient wSij.

Thus, in the present embodiment, the time series data of the input shaftrotation speed NT is included in the input variables of the detectionmapping. Accordingly, it becomes possible to detect the misfire thatreflects a delay until influence of the change in rotation speed of thetransmission input shaft 45 appears in the rotation behavior of thecrankshaft.

Third Embodiment

Hereinafter, a third embodiment will be described with the attentionmainly given to the differences from the first embodiment with referenceto the drawings.

In the present embodiment, the process of calculating the combustionstate variable PR is performed outside the vehicle. FIG. 5 shows thestate detection system according to the present embodiment. In FIG. 5,component members corresponding to those shown in FIG. 1 are designatedby the same numerals for convenience.

A controller 60 in a vehicle VC shown in FIG. 5 includes a communicationdevice 69. The communication device 69 is a device for communicatingwith a center 90 through a network 80 outside the vehicle VC. The center90 analyzes the data transmitted from a plurality of vehicles VC. Thecenter 90 includes a CPU 92, a ROM 94, a memory 96, a peripheral circuit97, and a communication device 99, which can communicate through a bus98. The memory 96 stores mapping data 96 a. In the present embodiment,the center 90 and the controller 60 of the vehicles VC constitute astate detection system.

FIGS. 6 and 7 show the procedures of the processes relating to a misfiredetection according to the present embodiment. The process shown in FIG.6 is implemented when the CPU 62 executes a misfire subprogram 64 bstored in the ROM 64 shown in FIG. 5. The process shown in FIG. 7 isimplemented when the CPU 92 executes a misfire main program 94 a storedin the ROM 94. The processes in FIGS. 6 and 7 corresponding to theprocess shown in FIG. 2 are designated by the same step numbers forconvenience. Hereinafter, based on the time series of the misfiredetection process, the processes shown in FIGS. 6 and 7 will bedescribed.

Specifically, in the vehicle VC, when positive determination is made inthe process of S14 shown in FIG. 6, the CPU 62 acquires minute rotationtime T30(0), T30(6), T30(12), T30(18), T30(24), T30(30), T30(36),T30(42), T30(48) (S50). These values of the minute rotation time T30constitute a rotation waveform variable that is a variable including theinformation regarding a difference between the values of the minuterotation time T30 at angular intervals different from each other.Particularly, the minute rotation time T30 is a period of time taken forrotation at an angular interval from 30° CA before a compression topdead center to the compression top dead center. The minute rotation timeT30 is a value corresponding to nine appearing timings of thecompression top dead center. Accordingly, group data of the minuterotation time T30 constitutes a variable indicating the informationregarding a difference between the values of the minute rotation timeT30 corresponding to the compression top dead center different from eachother. All of these nine values of the minute rotation time T30 are usedin calculation of the inter-cylinder ΔTb(2), and the fluctuation patternvariables FL[02], FL[12], FL[32].

Next, after executing the process of S22, the CPU 62 operates thecommunication device 69 to transmit the data acquired in the processesof S50, S22 to the center 90 together with identification informationregarding the vehicle VC (S52). In the following description, theidentification information regarding the vehicle VC is stated as avehicle ID.

In response, the CPU 92 of the center 90 receives the transmitted dataas shown in FIG. 7 (S60). The CPU 92 then substitutes the values of thevariables acquired in the process of S60 to input variables x(1) tox(13) (S62). Specifically, the CPU 92 substitutes the values of theminute rotation time T30(0), T30(6), T30(12), T30(18), T30(24), T30(30),T30(36), T30(42), T30(48) into the input variables x(1) to x(9),respectively. The CPU 92 also substitutes the value of the rotationspeed NE into the input variable x(10), the value of the chargingefficiency η into the input variable x(11), the value of the lock-uphydraulic pressure Plc into the input variable x(12), and the value ofthe input shaft rotation speed NT into the input variable x(13).

Next, the CPU 92 inputs the input variables x(1) to x(13) into adetection mapping that is defined by the mapping data 96 a stored in thememory 96 shown in FIG. 5 so as to calculate the value of the combustionstate variable PR that is an output value of the detection mapping(S64).

In the present embodiment, the detection mapping is constituted of aneural network having “α” intermediate layers and an output layer. Theintermediate layers each have activation functions h1 to hα that areReLU. The output layer has an activation function that is a softmaxfunction. For example, in a first intermediate layer, the values ofnodes are generated by inputting the input variables x(1) to x(13) intoa linear mapping defined by a coefficient w(1)ji (j=0 to n1 and i=0 to13) and inputting an obtained output into the activation function h1.Specifically, on the assumption that m=1, 2, . . . , α, the values ofnodes in m-th intermediate layer are generated by inputting an output ofa linear mapping defined by a coefficient w(m) into an activationfunction hm. In FIG. 7, n1, n2, . . . , nα are the number of nodes ineach of the first, second, . . . , α-th intermediate layers,respectively. Incidentally, the coefficient w(1)j0 or the like is a biasparameter, and the input variable x(0) is defined as “1”.

Next, the CPU 92 operates the communication device 99 to transmit asignal indicating the value of the combustion state variable PR to thevehicle VC to which the data received in the process of S60 wastransmitted (S66), and temporarily terminates a series of the processesshown in FIG. 7. In response to this, as shown in FIG. 6, the CPU 62receives the value of the combustion state variable PR (S54), andexecutes the processes of S28 to S38.

Thus, in the present embodiment, since the process in S64 is executed inthe center 90, the arithmetic load of the CPU 62 can be reduced.

Fourth Embodiment

Hereinafter, a fourth embodiment will be described with the attentionmainly given to the differences from the aforementioned embodiments withreference to the drawings.

The state detection system in each of the aforementioned embodiments isconfigured as a system that detects the state where a misfire occurs inthe internal combustion engine 10, based on the rotation fluctuation ofthe crankshaft 24. In the case where the air-fuel ratio varies betweenthe cylinders, and therefore air-fuel ratio imbalance between thecylinders occurs, the combustion states of the cylinders also vary,which causes increased rotation fluctuation of the crankshaft 24. Thestate detection system of the present embodiment is configured as asystem that detects such an air-fuel ratio imbalance between thecylinders. The configuration of the state detection system of thepresent embodiment is basically the same as the configuration shown inFIG. 1. However, the ROM 64 in the state detection system of the presentembodiment stores a program for detecting the air-fuel ratio imbalancebetween cylinders instead of the misfire program 64 a shown in FIG. 1.

FIG. 8 shows the procedures of the process regarding detection of theair-fuel ratio imbalance between the cylinders. The process shown inFIG. 8 is implemented when the CPU 62 repeatedly executes the detectionprogram stored in the ROM 64 in every predetermined control cycle.

In a series of the processes shown in FIG. 8, the CPU 62 firstdetermines whether or not an execution condition of the imbalancedetection process is established (S80). The execution condition includesthat purging of fuel vapor or recycling of exhaust gas with respect tointake air of the internal combustion engine 10 is not conducted.

Next, the CPU 62 acquires values of the minute rotation time T30(1), T30(2), . . . , T30(24), upstream-side averages Afuave(1), Afuave(2), . . ., Afuave(24), rotation speed NE, charging efficiency η, 0.5-orderamplitude Ampf/2, and lock-up hydraulic pressure Plc, and input shaftrotation speed NT (S82). When m=1 to 24, the upstream-side averageAfuave (m) is an average of the upstream-side detection values Afu at anangular interval of 30° CA that is the same as each of the minuterotation time T30(m). The 0.5-order amplitude Ampf/2 is the intensity ofa 0.5-order component of the rotational frequency of the crankshaft 24.The CPU 62 calculates the 0.5-order amplitude Ampf/2 by Fouriertransform of the time series data of the minute rotation time T30.

Next, the CPU 62 substitutes the values acquired in the process of S12into input variables x(1) to x(53) of a detection mapping that outputsan imbalance rate Riv (S84). More specifically, on the assumption that“m=1 to 24”, the CPU 62 substitutes the value of the minute rotationtime T30(m) into an input variable x(m), the value of the upstream-sideaverage Afuave(m) into the input variable x(24+m), the value of therotation speed NE into the input variable x(49), the value of thecharging efficiency into the input variable x(50), and the value of0.5-order amplitude Ampf/2 into the input variable x(51). The CPU 62also substitutes the value of the lock-up hydraulic pressure Plc intothe input variable x(52), and the value of the input shaft rotationspeed NT into the input variable x(53), respectively.

In the present embodiment, the imbalance rate Riv is “0” in the cylinderin which fuel of a target injection amount is injected. The imbalancerate Riv is a positive value when an actual injection amount is largerthan the target injection amount, whereas the imbalance rate Riv is anegative value when the actual injection amount is smaller than thetarget injection amount.

Next, the CPU 62 inputs the input variables x(1) to x(53) into thedetection mapping defined by the mapping data 66 a stored in the memory66 shown in FIG. 1 so as to calculate each of the imbalance rates Riv(1)to Riv(4) of the cylinder #i (i=1 to 4) (S86).

In the present embodiment, the detection mapping is constituted of aneural network having one intermediate layer. The neural networkincludes an activation function h(x) as an input-side nonlinear mappingthat performs nonlinear conversion of the outputs of an input-sidecoefficient wFjk (j=0 to n, k=0 to 53) and an input-side linear mappingthat is a linear mapping defined by the input-side coefficient wFjk. Inthe present embodiment, a hyperbolic tangent “tanh(x)” is illustrated asthe activation function h(x). The neural network includes the activationfunction f(x) as an output-side nonlinear mapping that performsnonlinear conversion of the outputs of an output-side coefficient wSij(i=1 to 4, j=0 to n) and an output-side linear mapping that is a linearmapping defined by the output-side coefficient wSij. In the presentembodiment, the hyperbolic tangent “tanh(x)” is illustrated as theactivation function f(x). The value n represents the dimension of theintermediate layer.

When the process of S86 is completed, or when negative determination ismade in the process of S80, the CPU 62 temporarily terminates a seriesof the processes shown in FIG. 8. FIG. 9 shows the procedures of theprocess using the imbalance rate Riv(i). The process shown in FIG. 9 isimplemented, when the CPU 62 repeatedly executes the handling programstored in the ROM 64 shown in FIG. 1 whenever the imbalance rate Riv(i)is calculated, for example.

In a series of the processes shown in FIG. 9, the CPU 62 first updatesthe imbalance learning value Liv(i) by an index moving average processthat takes, as an input, the value of the imbalance rate Riv(i) that isnewly calculated in the process of FIG. 8 (S90). Specifically, the CPU62 updates the imbalance learning value Liv with the sum of a valueobtained by multiplying a coefficient a by the imbalance learning valueLiv(i) stored in the memory 66 and a value obtained by multiplying “1-α”by the imbalance rate Riv(i) (S90). Note that “0<α<1.”

Next, the CPU 62 determines whether or not the imbalance learning valueLiv(i) is equal to or more than a lean-side tolerance limit LL and isequal to or less than a rich-side tolerance limit LH (S92). Whendetermining that the imbalance learning value Liv(i) is less than thelean-side tolerance limit LL, or is larger than the rich-side tolerancelimit LH (S92: NO), the CPU 62 operates an alarm lamp 78 to execute thenotification process in order to encourage a user to make repairs (S94).

Meanwhile, when determining that the imbalance learning value Liv(i) ismore than the lean-side tolerance limit LL, and is equal to or less thanthe rich-side tolerance limit LH (S92: YES), or when the process of S94is completed, the CPU 62 corrects a request injection amount Qd (#i) ofeach cylinder (S96). Specifically, the CPU 62 corrects the requestinjection amount Qd (#i) by adding a correction amount ΔQd (Liv(i))corresponding to the imbalance learning value Liv(i) to the requestinjection amount Qd (#i) of each cylinder. Here, when the imbalancelearning value Liv(i) is larger than zero, the correction amount ΔQd(Liv(i)) is a negative value, whereas when the imbalance learning valueLiv(i) is smaller than zero, the correction amount ΔQd (Liv(i)) is apositive value. When the imbalance learning value Liv(i) is zero, thecorrection amount ΔQd (Liv(i)) becomes zero either.

The CPU 62 temporarily terminates a series of the processes shown inFIG. 9, when the process of S96 is completed. In the present embodiment,when positive determination is made in the process of S80, and then theprocess of S82 is executed, the process of S96 is temporarily stopped.

Incidentally, the mapping data 66 a in the present embodiment isgenerated as shown below, for example. First, based on measurementperformed in advance using a single unit, a plurality of fuel injectionvalves 20 that present various values other than zero as the imbalancerate Riv, and three fuel injection valves 20 that present zero as theimbalance rate are prepared. Then, an internal combustion engine 10,coupled with a torque converter 40 and mounted with three fuel injectionvalves 20 that present zero as the imbalance rate and one fuel injectionvalve 20 that presents the imbalance rate other than zero, is operatedin a test bench with the output shaft of the torque converter 40 beingconnected to a dynamometer. The imbalance rates Rivt of the mounted fuelinjection valves 20 are each used as teacher data.

With use of the rotation waveform variable acquired each time and thevalue acquired in the process of S82, the value of the imbalance rateRivt is calculated by the same processes as in S84, S86. The values ofthe input-side coefficient wFjk and the output-side coefficient wSij arelearned, so as to reduce a difference between the thus-learned imbalancerate Rivt and the teacher data. Specifically, the values of theinput-side coefficient wFjk and the output-side coefficient wSij may belearned so as to minimize cross entropy, for example. The rotation speedof the transmission input shaft 45 can be imitated with the rotationspeed of the dynamometer.

In the present embodiment, the lock-up hydraulic pressure Plc and theinput shaft rotation speed NT are included in the input of the detectionmapping. Accordingly, the imbalance rate Rivt can be calculated as avalue reflecting the influence that the drive system of the vehicle VCexerts on the rotation behavior of the crankshaft 24. Therefore, it ispossible to enhance the detection accuracy of the air-fuel ratioimbalance between cylinders in the internal combustion engine 10 mountedon the vehicle VC.

Correspondence Relation

The memory corresponds to the memory 66. The rotation waveform variablecorresponds to the inter-cylinder variable ΔTb(2), the fluctuationpattern variables FL[02], FL[12], FL [32]. The first processorcorresponds to the CPU 62 and the ROM 64. The second processorcorresponds to the CPU 92 and the ROM 94. The acquisition processcorresponds to the processes of S50, S22, S22′, S82, and thevehicle-side reception process corresponds to the process of S54,respectively. The outer-side reception process corresponds to theprocess of S60, the output value calculation process corresponds to theprocesses of S62, S64, S86, the outer-side transmission processcorresponds to the process of S66, and the determination processcorresponds to the processes of S28, S30, S34, S92, respectively. Thedata analysis device corresponds to the center 90. The rotation speed ofthe drive system rotating element that is a rotating element disposed inthe power transmission line between the internal combustion engine 10and the driving wheels 50 corresponds to the input shaft rotation speedNT. The drive system rotating element corresponds to the transmissioninput shaft 45. In the first, third, and fourth embodiments, the inputshaft rotation speed NT corresponds to the drive system rotation speedvariable.

In the first, second, and third embodiments, the state where a misfirehas occurred corresponds to the predetermined operating state. In thefourth embodiment, the state where an air-fuel ratio varies between thecylinders corresponds to the predetermined operating state. Furthermore,in the fourth embodiment, the imbalance rate Rivt corresponds to thecombustion state variable.

Other Embodiments

The present embodiment can be implemented with modifications as shownbelow. The present embodiment and following modifications may beimplemented in combination with each other without departing from therange of technically consistency.

Inter-Cylinder Variable

The inter-cylinder variable ΔTb is not limited to a difference betweenvalues of the minute rotation time T30 corresponding to the compressiontop dead centers of a pair of cylinders that are adjacent in appearingtiming of the compression top dead center to each other, the differencebeing a difference between the values separated by 720° CA. For example,the inter-cylinder variable ΔTb may be a difference between values ofminute rotation time T30 corresponding to the compression top deadcenters of the cylinders having the appearance timing of the compressiontop dead center being separated by 360° CA from each other, thedifference being a difference of the values separated by 720° CA. Inthis case, the inter-cylinder ΔTb(2) is equal to“T30(12)-T30(24)-{T30(36)-T30(48)}”.

The inter-cylinder variable ΔTb is not limited to the difference betweenvalues of the minute rotation time T30 corresponding to the compressiontop dead centers of a pair of cylinders, the values being a differenceof the values separated by 720° CA. The inter-cylinder variable ΔTb maybe a difference between values of the minute rotation time T30corresponding to the compression top dead centers of a cylinder as amisfire detection target and a cylinder other than the cylinder as themisfire detection target.

For example, the inter-cylinder variable may be a ratio between valuesof the minute rotation time T30 corresponding to the compression topdead centers of a pair of cylinders. The minute rotation time used fordefining the inter-cylinder variable ΔTb is not limited to the timetaken for rotation of 30° CA. For example, the minute rotation time maybe the time taken for rotation of 45° CA, or the like. In that case, itis desirable that the minute rotation time is the time taken forrotation at an angular interval equal to or less than the interval ofappearance of the compression top dead center.

Furthermore, in the above configuration, an instant rotation speed,obtained by dividing a prescribed angular interval by the time taken forrotation at the prescribed angular interval, may be used instead of theminute rotation time.

Fluctuation Pattern Variable

Definition of the fluctuation pattern variable is not limited to thedefinition illustrated in the embodiments disclosed. For example, thedefinition of the fluctuation pattern variable may be changed bychanging the inter-cylinder variable ΔTb to the variable illustrated inthe column “Inter-Cylinder Variable” or other variables.

Furthermore, it is not essential to define the fluctuation patternvariable as a ratio between values of the inter-cylinder variable ΔTbcorresponding to the appearance timings of the compression top deadcenter that are different from each other. The fluctuation patternvariable may be a difference instead of the ratio. In this case,including the operating point variable of the internal combustion engine10 in an input also makes it possible to calculate the value of thecombustion state variable PR that reflects that the size of thefluctuation pattern variable changes in accordance with the operatingpoint.

Drive System Rotation Speed Variable

A mapping including, as an input variable, a variable indicating theseries data of the input shaft rotation speed NT as in the secondembodiment may be used as the detection mapping in the third embodimentand the fourth embodiment. Moreover, the input shaft rotation speed NTmay be replaced with the rotation speed of a drive system rotatingelement, other than the transmission input shaft 45 disposed in thepower transmission line between the internal combustion engine 10 andthe driving wheels 50, such as the output shaft speed Nout that is therotation speed of the transmission output shaft 46, and the wheel speedV that is the rotation speed of the driving wheels 50. The transmissionmode of torque among the transmission input shaft 45, the driving wheels50 and the crankshaft 24 changes in accordance with gear ratio settingof the change gear 44 that is interposed therebetween. Accordingly, whenthe variable, indicating the information on the rotation speed of thedrive system rotating element configured such that the change gear 44 isinterposed between the drive system rotating element and the crankshaft24, is included in the input variables of the detection mapping, it isdesirable that the information relating to the gear ratio of the changegear 44 is also included in the input variables of the detectionmapping.

Lock-up Hydraulic Pressure

In the embodiments disclosed, the lock-up hydraulic pressure Plc isacquired from the output of the oil pressure sensor 73 provided in thehydraulic circuit 48. However, the lock-up hydraulic pressure Plc may beacquired from an operation signal MS4 of the hydraulic circuit 48. Insuch a case, the oil pressure sensor 73 may be omitted.

In the embodiments disclosed, the lock-up hydraulic pressure Plc isincluded in the input variables of the detection mapping. Instead of thelock-up hydraulic pressure Plc, other variables indicating the operatingstate of the lock-up clutch 42 may be included in the input variables ofthe detection mapping. For example, when the operating state of thelock-up clutch 42 can be switched between an engaged state and adisengaged state in a binary manner, a variable indicating in whichstate the lock-up clutch 42 is can be used as a variable alternative tothe lock-up hydraulic pressure Plc. Incidentally, in the case of avehicle without the lock-up clutch 42, it is naturally understood thatthe variable indicating the operating state of the lock-up clutch 42 isnot included in the input variables of the detection mapping.

Rotation Waveform Variable

In the process of S26, the inter-cylinder variable ΔTb(2), and thefluctuation pattern variables FL[02], FL[12], FL[32] constitute therotation waveform variable. However, the rotation waveform variable isnot limited to this configuration. For example, the fluctuation patternvariables that constitute the rotation waveform variable may be any oneor two of the fluctuation pattern variables FL[02], FL[12], FL[32]. Thefluctuation pattern variables may also include four or more fluctuationpattern variables, such as the fluctuation pattern variables FL[02],FL[12], FL[32], FL[42].

In the process of S64, the values of the minute rotation time T30corresponding to each of the nine timings that are different inappearance timing of the compression top dead center from each otherconstitute the rotation waveform variable. However, the rotationwaveform variable is not limited to this configuration. For example,with use of the compression top dead center of the cylinder to be atarget of misfire detection as a center, a section twice or above theangular interval where the compression top dead center appears isdivided into subsections at intervals of 30° CA, and the value of theminute rotation time T30 in each of the subsections may constitute therotation waveform variable. In the above configuration, it is notessential to use the compression top dead center of the cylinder to be amisfire detection target as a center. Furthermore, the minute rotationtime is not limited to the time taken for rotation at intervals of 30°CA. Instead of the minute rotation time, an instant rotation speed,obtained by dividing a prescribed angular interval by the time taken forrotation at the prescribed angular interval, may be used.

Operating Point Variable

The operating point variable is not limit to the rotation speed NE andthe charging efficiency η. For example, the operating point variable maybe an intake air amount Ga and the rotation speed NE. When a compressionignition type internal combustion engine is used as stated in the columnof “Internal Combustion Engine” below, the operating point variable maybe an injection amount and the rotation speed NE. It is not essential touse the operating point variable as an input of the detection mapping.For example, in such a case where the internal combustion engine isdriven exclusively in a specific operating point when the system isapplied to an internal combustion engine mounted on a series hybridvehicle described in the column of “Vehicle” below, the value of thecombustion state variable PR can be calculated with high accuracywithout the operating point variable being included in the inputvariables.

Outer-Side Transmission Process

In the process of S66, the value of the combustion state variable PR istransmitted. However, the value to be transmitted is not limited to thecombustion state variable PR. For example, the values of the prototypevariables yR(1), yR (2) used as an input of the softmax function servingas an output activation function may be transmitted. For example, thecenter 90 may execute the processes of S28 to S36, and transmit thedetermination result regarding whether or not there is any abnormality.

Handling Process

In the embodiments disclosed, the alarm lamp 78 is operated to notifythe occurrence of a misfire through visual information. However, thenotification method is not limited to this. For example, a speaker maybe operated to notify the occurrence of a misfire through auditoryinformation. For example, the controller 60 shown in FIG. 1 may includethe communication device 69, and a process of transmitting to a user'smobile terminal a signal indicating the occurrence of a misfire throughoperation of the communication device 69 may be provided. The processcan be implemented by installing on the user's mobile terminal anapplication program for executing the notification.

The handling process is not limited to the notification process. Forexample, the handling process may be an operation process that is tooperate an operation unit, configured to control combustion of air-fuelmixture in the combustion chambers 18 of the internal combustion engine10, in accordance with the information indicating the occurrence of amisfire. Specifically, for example, each of the ignition devices 22 maybe used as the operation unit, and the operation unit of the cylinder,in which the misfire occurred, may advance the ignition timing. Forexample, each of the fuel injection valves 20 may be used as theoperation unit, and the operation unit of the cylinder, in which themisfire occurred, may increase the fuel injection amount.

Input into Detection Mapping

An input such as an input into the neural network and an input into aregression described in the column of “Algorithm of Machine Learning”below is not limited to an input constituted of physical values orfluctuation pattern variables FL which are single in each dimension. Forexample, some of a plurality of types of physical values or fluctuationpattern variables FL, used as an input into the detection mapping in theabove embodiments and the like, may be subjected to analysis ofprincipal components, instead of being used as a direct input into theneural network or the regression, and some of the principal componentsthereof may be used as a direct input into the neural network or theregression. However, when the principal components are used as an inputinto the neural network or the regression, it is not essential that theprincipal components are used as only a portion of the input into theneural network of the regression. Rather, the entire input may be madeup of the principal components. When the principal components are usedas an input into the detection mapping, the mapping data 66 a, 96 ainclude data for defining a detection mapping that defines the principalcomponents.

Mapping Data

The mapping data that defines mappings used for calculation executed inthe vehicle may be defined as the data that defines the mappingillustrated in the process of S64.

For example, according to the description in FIG. 7, the neural networkhas two or more intermediate layers. However, the number of theintermediate layers is not limited to this. In the embodimentsdisclosed, the activation functions h, h1, h2, . . . hα are set to ReLU,and the output activation function is set to the softmax function.However, the activation functions are not limited to this. For example,the activation functions h, h1, h2, . . . hα may be hyperbolic tangentfunctions. For example, the activation functions h, h1, h2, . . . hα maybe logistic sigmoid functions.

For example, the output activation functions may be logistic sigmoidfunctions. In this case, for example, an output layer may have one node,and an output variable may be the combustion state variable PR. If thatis the case, the presence or absence of abnormality can be determinedsuch that when the value of the output variable is equal to or greaterthan a prescribed value, abnormality is determined.

Algorithm of Machine Learning

The algorithm of machine learning is not limited to those using theneural network. For example, a regression may also be used. Theregression corresponds to the neural network without any intermediatelayer. A support vector machine may also be used, for example. In thiscase, there is no meaning in the size of the value of an output itself.Whether a misfire occurred or not is expressed based on whether thevalue is positive or not. In other words, the combustion state variablehas a value of three or more, and the size of these values do notexpress the magnitude of the probability of a misfire.

Learning Step

Learning is executed in the situation where a misfire occurs at randomin the embodiments disclosed. However, learning is not necessarilyexecuted in this situation. For example, learning may be executed in thesituation where a misfire continuously occurs in a specific cylinder.However, in that case, it is desirable that the inter-cylinder variableused as an input into the mapping or the inter-cylinder variable ΔTbused for fluctuation pattern variable is a different, or the like,between the values of the minute rotation time T30 corresponding to thecompression top dead centers of a cylinder to be a misfire detectiontarget and a cylinder other than the target cylinder, as stated in thecolumn of “Inter-Cylinder Variable”.

Learning is not limited to the learning based on the rotation behaviorof the crankshaft 24 when the internal combustion engine 10 is operated,with the crankshaft 24 being connected to a dynamometer. For example,learning may be performed based on the rotation behavior of thecrankshaft 24 when the internal combustion engine 10 is mounted on avehicle, and the vehicle is made to travel. With this configuration, theinfluence that the state of the road surface, on which the vehicletravels, exerts on the rotation behavior of the crankshaft 24 can bereflected on learning.

Data Analysis Device

For example, instead of the processes of S62, S64, the processes of S24,S26, or the like, may be executed in the center 90.

The process of FIG. 7 may be executed, for example, with the mobileterminal possessed by a user. This can be achieved by installing on themobile terminal an application program for executing the process of FIG.7. In this case, the process of transmitting and receiving the vehicleID may be deleted by setting such that an effective distance of datatransmission in the process of S52 is about the length of the vehicle,for example.

Processor

The processor is not limited to those including the CPU 62(92) and ROM64(94) and configured to execute software processing. For example, thesystem may include a dedicated hardware circuit (for example, an ASIC,etc.) for hardware processing of at least some of the processes that areprocessed by software in the embodiments disclosed. Specifically, theprocessor may have any one of the configurations (a) to (c): (a)including a processing device that executes all the processes based onprograms, and a program storage device such as a ROM that stores theprograms; (b) including a processing device that executes some of theprocesses based on programs, a program storage device, and a dedicatedhardware circuit that executes the remaining processes; and (c)including a dedicated hardware circuit that executes all the processes.Here, the number of the software processors including a processingdevice and a program storage device, or the number of the dedicatedhardware circuits may be two or more.

Memory

In the embodiments disclosed, the memory that stores the mapping data 66a, 96 a, and the memory (ROMs 64, 94) that stores the misfire program 64a and the misfire main program 94 a are provided as separate units.However, the memory may have other configurations.

Computer

The computer is not limited to those constituted of a processor such asthe CPU 62 and the ROM 64 mounted on a vehicle, and a processor such asthe CPU 92 and the ROM 94 included in the center 90. For example, thecomputer may be constituted of a processor mounted on a vehicle, aprocessor included in the center 90, and a processor such as a CPU and aROM in a user's mobile terminal. This configuration can be achieved by,for example, setting the process of S66 in FIG. 7 as a process oftransmitting to the user's mobile terminal, and setting the processes ofS54, S28 to S36 to be executed in the mobile terminal.

Predetermined Operating State

The operating states of the internal combustion engine 10 other than themisfire or the air-fuel ratio imbalance between cylinders may also beused as a detection target of the state detection system, as long as theoperating states involve variation in combustion state betweencylinders. For example, when so-called compression insufficiency, thatis, compression of intake air in the cylinder becoming insufficient dueto the intake valve or the exhaust valve being opened and fixed, occursin a specific cylinder, the combustion state varies between thecylinders, which causes increased rotation fluctuation of the crankshaft24. Accordingly, detecting such compression insufficiency with use ofthe detection mapping that takes the aforementioned rotation waveformvariable and the drive system rotation speed variable as an input makesit possible to detect the compression insufficiency with high accuracyby taking the influence that the drive states of the motor-generatorsexert on the rotation behavior of the crankshaft 24 into account.

Internal Combustion Engine

In the embodiments disclosed, the cylinder injection valves that injectfuel into the combustion chambers 18 are illustrated as the fuelinjection valves. However, the fuel injection valves are not limited tothe cylinder injection valves. For example, the fuel injection valvesmay be port injection valves that inject fuel into the intake passage12. Moreover, the internal combustion engine may have both the portinjection valves and the cylinder injection valves, for example.

The internal combustion engine is not limited to the spark ignition typeinternal combustion engine. For example, other internal combustionengines such as a compression ignition type internal combustion enginethat uses light oil as fuel may also be used.

Vehicle

Although the vehicle VC in the embodiments disclosed is configured suchthat the drive system includes the lock-up clutch 42, the torqueconverter 40, and the change gear 44, the drive system may have adifferent configuration.

What is claimed is:
 1. A state detection system for an internalcombustion engine, the state detection system being applied to theinternal combustion engine mounted on a vehicle, the state detectionsystem being configured to detect a predetermined operating state of theinternal combustion engine, the predetermined operating state involvinga variation in a combustion state between cylinders, the state detectionsystem comprising: a memory configured to store mapping data, themapping data being data that defines a detection mapping, the detectionmapping being a mapping between an input and an output, the input beinga rotation waveform variable and a drive system rotation speed variableand the output being a value of a combustion state variable, and thedetection mapping including a joint operation of the rotation waveformvariable and the drive system rotation speed variable based on aparameter learned by machine learning, the rotation waveform variablebeing a variable including information on a difference in rotation speedof a crankshaft between the cylinders of the internal combustion engineduring a period when combustion torque is generated in each of thecylinders, the drive system rotation speed variable being a variableindicating information on a rotation speed of a drive system rotatingelement that is a rotating element disposed in a power transmission linebetween the internal combustion engine and driving wheels, thecombustion state variable being a variable relating to a variationdegree in combustion state between the cylinders; and a processorconfigured to execute an acquisition process and a determinationprocess, the acquisition process being configured to acquire a value ofthe rotation waveform variable based on an output of a sensor thatdetects rotation behavior of the crankshaft and to acquire a value ofthe drive system rotation speed variable based on an output of a sensorthat detects rotation behavior of the drive system rotating element, thedetermination process being configured to determine whether or not theinternal combustion engine is in the predetermined operating state,based on an output value of the detection mapping that takes the valueof the rotation waveform variable and the value of the drive systemrotation speed variable acquired in the acquisition process as an input.2. The state detection system according to claim 1, wherein thepredetermined operating state is a state where a misfire has occurred.3. The state detection system according to claim 1, wherein thepredetermined operating state is a state where an air-fuel ratio variesbetween the cylinders.
 4. The state detection system according to claim1, wherein the drive system rotating element is a transmission inputshaft.
 5. The state detection system according to claim 1, wherein thedrive system rotation speed variable is a variable indicating timeseries data of the rotation speed of the drive system rotating element.6. The state detection system according to claim 1, wherein when it isdetermined by the determination process that the internal combustionengine is in the predetermined operating state, the processor isconfigured to operate prescribed hardware to execute a handling processfor handling the predetermined operating state.
 7. The state detectionsystem according to claim 1, wherein: the determination process includesan output value calculation process for calculating an output value ofthe detection mapping that takes the value of the rotation waveformvariable and the value of the drive system rotation speed variableacquired in the acquisition process as an input; the processor includesa first processor mounted on the vehicle, and a second processordisposed outside the vehicle; the first processor is configured toexecute the acquisition process and a vehicle-side reception process forreceiving a signal based on a calculation result of the output valuecalculation process; and the second processor is configured to executethe output value calculation process and an outer-side transmissionprocess for transmitting to the vehicle a signal based on thecalculation result of the output value calculation process.
 8. The statedetection system according to claim 7, further comprising a dataanalysis device, wherein the second processor and the memory areconstituent elements of the data analysis device.
 9. The state detectionsystem according to claim 7, further comprising the vehicle.
 10. A dataanalysis device for an internal combustion engine, the data analysisdevice being configured to detect a predetermined operating state of aninternal combustion engine, the predetermined operating state involvinga variation in a combustion state between cylinders, the data analysisdevice comprising: a memory configured to store mapping data, themapping data being data that defines a detection mapping, the detectionmapping being a mapping between an input and an output, the input beinga rotation waveform variable and a drive system rotation speed variableand the output being a value of a combustion state variable, and thedetection mapping including a joint operation of the rotation waveformvariable and the drive system rotation speed variable based on aparameter learned by machine learning, the rotation waveform variablebeing a variable including information on a difference in rotation speedof a crankshaft between the cylinders of the internal combustion engineduring a period when combustion torque is generated in each of thecylinders, the drive system rotation speed variable being a variableindicating information on a rotation speed of a drive system rotatingelement that is a rotating element disposed in a power transmission linebetween the internal combustion engine and driving wheels, thecombustion state variable being a variable relating to a variationdegree in combustion state between the cylinders; and a processorconfigured to execute an acquisition process and a determinationprocess, the acquisition process being configured to acquire a value ofthe rotation waveform variable based on an output of a sensor thatdetects rotation behavior of the crankshaft and to acquire a value ofthe drive system rotation speed variable based on an output of a sensorthat detects rotation behavior of the drive system rotating element, thedetermination process being configured to determine whether or not theinternal combustion engine is in the predetermined operating state,based on an output value of the detection mapping that takes the valueof the rotation waveform variable and the value of the drive systemrotation speed variable acquired in the acquisition process as an input.11. A vehicle comprising: an internal combustion engine; and pg,41 astate detection system configured to detect a predetermined operatingstate of the internal combustion engine, the predetermined operatingstate involving a variation in a combustion state between cylinders, thestate detection system including: a memory configured to store mappingdata, the mapping data being data that defines a detection mapping, thedetection mapping being a mapping between an input and an output, theinput being a rotation waveform variable and a drive system rotationspeed variable and the output being a value of a combustion statevariable, and the detection mapping including a joint operation of therotation waveform variable and the drive system rotation speed variablebased on a parameter learned by machine learning, the rotation waveformvariable being a variable including information on a difference inrotation speed of a crankshaft between the cylinders of the internalcombustion engine during a period when combustion torque is generated ineach of the cylinders, the drive system rotation speed variable being avariable indicating information on a rotation speed of a drive systemrotating element that is a rotating element disposed in a powertransmission line between the internal combustion engine and drivingwheels, the combustion state variable being a variable relating to avariation degree in combustion state between the cylinders, and aprocessor configured to execute an acquisition process and adetermination process, the acquisition process being configured toacquire a value of the rotation waveform variable based on an output ofa sensor that detects rotation behavior of the crankshaft and to acquirea value of the drive system rotation speed variable based on an outputof a sensor that detects rotation behavior of the drive system rotatingelement, the determination process being configured to determine whetheror not the internal combustion engine is in the predetermined operatingstate, based on an output value of the detection mapping that takes thevalue of the rotation waveform variable and the value of the drivesystem rotation speed variable acquired in the acquisition process as aninput.